Microsoft, Facebook Go All In On Machine Learning

Mobile is officially dead. Long live Machine Learning and AI! At least so says Microsoft’s 2017 Vision statement. They’ve made it pretty clear that they’re now all in on Machine Learning with there being zero references to mobile. Only a year ago mobile and cloud was their main strategy but things move fast in tech. As you can see it’s out with the old…

Our strategy is to build best-in-class platforms and productivity services for a mobile-first, cloud-first world. – Microsoft Form 10K 2016

In with the new!

Our strategy is to build best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with artificial intelligence (“AI”). – Microsoft Form 10K 2017

It’s a nice, clean swap out from mobile to machine learning and AI. Given Microsoft essentially missed the entire “mobile” era one can only wonder if they’ll do the same for AI. Google, Facebook and others are already integrating AI into the very core of their business. Microsoft does has a very strong AI research division but this is only one part. If they don’t pivot their core products to leverage AI they will once again miss out. Outmaneuvered by rivals who are already far ahead like Apple, Google and Facebook.

Facebook Machine Learning Translation

Speaking of integrating AI into your core products, Facebook has transitioned entirely to using neural machine translation for it’s language translation. They outlined the benefits of the new system in a blog post this week. The system will be responsible for over 4.5 billion translations each day!

We recently switched from using phrase-based machine translation models to neural networks to power all of our backend translation systems, which account for more than 2,000 translation directions and 4.5 billion translations each day. These new models provide more accurate and fluent translations, improving people’s experience consuming Facebook content that is not written in their preferred language.

Old vs New – An example result from Facebook

Our previous phrase-based statistical techniques were useful, but they also had limitations. One of the main drawbacks of phrase-based systems is that they break down sentences into individual words or phrases, and thus when producing translations they can consider only several words at a time. This leads to difficulty translating between languages with markedly different word orderings.

It’s not surprising Facebook’s moved in this direction. It’s easy to understand that AI will be more accurate if it translates full sentences rather than individual words. Translation is becoming progressively more and more important as new areas of the world begin to access the Internet. There are millions of existing helpful resources that only exist in English. Having instant, top quality level translations for both parties when communicating is also vital.

Do you think Microsoft has already missed the AI boat? Let us know in the comments below!

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